Journal of Otolaryngology and Ophthalmology of Shandong University ›› 2026, Vol. 40 ›› Issue (1): 112-119.doi: 10.6040/j.issn.1673-3770.0.2023.470

• Review • Previous Articles    

Research progress and prospect analysis of deep learning technology in the application of pharyngeal and laryngeal endoscopy

CHENG Zhuo1,2, LIANG Hui2, XING Lumin3   

  1. 1. Department of Otorhinolaryngology & Head and Neck Surgery, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan 250021, Shandong, China2. Department of Otorhinolaryngology & Head and Neck Surgery, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, Shandong, China3. Department of Information, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong, Jinan 250014, Shandong, China
  • Published:2026-02-13

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Abstract: The emergence of deep learning has played a huge role in the promotion of medical quality, especially in the advancement of medical examination, and some areas of otolaryngology and head and neck surgery have benefited from it. On the basis of deep learning, the field of endoscopic analysis of the pharynx and larynx has made very effective attempts in the past five years. This article discusses the research and related research based on deep learning in pharyngeal and laryngeal endoscopic application in the past five years, analyzes the research progress in this field, and divides its development stage into three stages: the stage of neural network germination, the blending of neural network and medicine, and the development of neural network applicability. Based on clinical, sample information and other three aspects, this article discusses current research bottlenecks, expounds possible solutions and development prospects in the future, points out the main obstacles in the application of deep learning in current pharyngeal and laryngeal endoscopic research, and gives a possible development trend outlook in multiple aspects such as multicenter research, multitask learning, high-level data information collection in the future.

Key words: Pharyngeal and laryngeal endoscopy, artificial Intelligence, deep learning, Otorhinolaryngology head and neck surgery, Computer-assisted diagnosis

CLC Number: 

  • R762
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